When Does Sora Show:The Beginning of TAO to Imaginative Intelligence and Scenarios Engineering

DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in the direction of Imaginative Intelligence(II),i.e.,something similar to automatic wordsto-videos generation or intelligent digital movies/theater technology that could be used for conducting new“Artificiofactual Experiments”[2]to replace conventional“Counterfactual Experiments”in scientific research and technical development for both natural and social studies[2]-[6].Now we have OpenAI’s Sora,so soon,but this is not the final,actually far away,and it is just the beginning.

Topology and Semantic Information Fusion Classification Network Based on Hyperspectral Images of Chinese Herbs

Most methods for classifying hyperspectral data only consider the local spatial relation-ship among samples,ignoring the important non-local topological relationship.However,the non-local topological relationship is better at representing the structure of hyperspectral data.This paper proposes a deep learning model called Topology and semantic information fusion classification network(TSFnet)that incorporates a topology structure and semantic information transmis-sion network to accurately classify traditional Chinese medicine in hyperspectral images.TSFnet uses a convolutional neural network(CNN)to extract features and a graph convolution network(GCN)to capture potential topological relationships among different types of Chinese herbal medicines.The results show that TSFnet outperforms other state-of-the-art deep learning classification algorithms in two different scenarios of herbal medicine datasets.Additionally,the proposed TSFnet model is lightweight and can be easily deployed for mobile herbal medicine classification.

Research on Breeze Vibration Law and Modal Identification Method of Conductor Considering Anti-Vibration Hammer Damage

In the harsh environment,the structural health of the anti-vibration hammer,which suffers from the coupled effects of corrosion and fatigue damage,is significantly reduced.As part of the conductor structure,the anti-vibration hammer is rigidly attached to the conductor,effectively suppressing conductor vibration.The conductor’s breeze vibration law and natural modal frequency are altered damage to the anti-vibration hammer structure.Through built a vibration experiment platform to simulate multiple faults such as anti-vibration hammer head drop off and position slippage,which to obtained the vibration acceleration signal of the conductor.The acceleration vibration signal is processed and analyzed in the time and frequency domains.The results are used to derive the breeze vibration law of the conductor under multiple faults and propose an anti-vibration hammer damage online monitoring technology.The results show that the vibration acceleration value and vibration intensity of the conductor are significantly increased after the anti-vibration hammer damage.The natural frequency increases for each order,with an absolute change ranging from 0.15 to 6.49 Hz.The anti-vibration hammer slipped due to a loose connection,the 1st natural frequency increases from 8.18 to 16.62 Hz.Therefore,in engineering applications,there can be no contact to determine the anti-vibration hammer damage situation by monitoring the modal natural frequency of the conductor.This is even a tiny damage that cannot be seen.This method will prevent the further expansion of the damage that can cause accidents.

Growth behaviors and emission properties of Co-deposited MAPbI_(3) ultrathin films on MoS_(2)

Hybrid organic–inorganic perovskite thin films have attracted much attention in optoelectronic and information fields because of their intriguing properties. Due to quantum confinement effects, ultrathin films in nm scale usually show special properties. Here, we report on the growth of methylammonium lead iodide(MAPbI_(3)) ultrathin films via co-deposition of PbI_2 and CH_3NH_3I(MAI) on chemical-vapor-deposition-grown monolayer MoS_(2) as well as the corresponding photoluminescence(PL) properties at different growing stages. Atomic force microscopy and scanning electron microscopy measurements reveal the MoS_(2) tuned growth of MAPbI_(3) in a Stranski–Krastanov mode. PL and Kelvin probe force microscopy results confirm that MAPbI_(3) /MoS_(2) heterostructures have a type-Ⅱ energy level alignment at the interface. Temperaturedependent PL measurements on layered MAPbI_(3) (at the initial stage) and on MAPbI_(3) crystals in averaged size of 500 nm(at the later stage) show rather different temperature dependence as well as the phase transitions from tetragonal to orthorhombic at 120 and 150 K, respectively. Our findings are useful in fabricating MAPbI_(3) /transition-metal dichalcogenide based innovative devices for wider optoelectronic applications.

Modeling and Analysis of the Impacts of Temporal-Spatial Variant Troposphere on Ground-Based SAR Imaging of Asteroids

The near-Earth asteroid collisions could cause catastrophic disasters to humanity and the Earth,so it is crucial to monitor asteroids.Ground-based synthetic aperture radar(SAR)is an observation technique for high resolution imaging of asteroids.The ground-based SAR requires a long integration time to achieve a large synthetic aperture,and the echo signal will be seriously affected by temporal-spatial variant troposphere.Traditional spatiotemporal freezing tropospheric models are ineffective.To cope with this,this paper models and analyses the impacts of temporal-spatial variant troposphere on ground-based SAR imaging of asteroids.For the background tropo-sphere,a temporal-spatial variant ray tracing method is proposed to trace the 4D(3D spatial+temporal)refractive index network provided by the numerical weather model,and calculate the error of the background troposphere.For the tropospheric turbulence,the Andrew power spectral model is used in conjunction with multiphase screen theory,and varying errors are obtained by tracking the changing position of the pierce point on the phase screen.Through simulation,the impact of temporal-spatial variant tropospheric errors on image quality is analyzed,and the simulation results show that the X-band echo signal is seriously affected by the troposphere and the echo signal must be compensated.

Robust adaptive radar beamforming based on iterative training sample selection using kurtosis of generalized inner product statistics

In engineering application,there is only one adaptive weights estimated by most of traditional early warning radars for adaptive interference suppression in a pulse reputation interval(PRI).Therefore,if the training samples used to calculate the weight vector does not contain the jamming,then the jamming cannot be removed by adaptive spatial filtering.If the weight vector is constantly updated in the range dimension,the training data may contain target echo signals,resulting in signal cancellation effect.To cope with the situation that the training samples are contaminated by target signal,an iterative training sample selection method based on non-homogeneous detector(NHD)is proposed in this paper for updating the weight vector in entire range dimension.The principle is presented,and the validity is proven by simulation results.

SAC-Based Computation Offloading for Reconfigurable Intelligent Surface-Aided Mobile Edge Networks

In this paper,we concentrate on a reconfigurable intelligent surface(RIS)-aided mobile edge computing(MEC)system to improve the offload efficiency with moving user equipments(UEs).We aim to minimize the energy consumption of all UEs by jointly optimizing the discrete phase shift of RIS,UEs’transmitting power,computing resources allocation,and the UEs’task offloading strategies for local computing and offloading.The formulated problem is a sequential decision making across multiple coherent time slots.Furthermore,the mobility of UEs brings uncertainties into the decision-making process.To cope with this challenging problem,the deep reinforcement learning-based Soft Actor-Critic(SAC)algorithm is first proposed to effectively optimize the discrete phase of RIS and the UEs’task offloading strategies.Then,the transmitting power and computing resource allocation can be determined based on the action.Numerical results demonstrate that the proposed algorithm can be trained more stably and perform approximately 14%lower than the deep deterministic policy gradient benchmark in terms of energy consumption.

Delay-optimal multi-satellite collaborative computation offloading supported by OISL in LEO satellite network

By deploying the ubiquitous and reliable coverage of low Earth orbit(LEO)satellite networks using optical inter satel-lite link(OISL),computation offloading services can be provided for any users without proximal servers,while the resource limita-tion of both computation and storage on satellites is the impor-tant factor affecting the maximum task completion time.In this paper,we study a delay-optimal multi-satellite collaborative computation offloading scheme that allows satellites to actively migrate tasks among themselves by employing the high-speed OISLs,such that tasks with long queuing delay will be served as quickly as possible by utilizing idle computation resources in the neighborhood.To satisfy the delay requirement of delay-sensi-tive task,we first propose a deadline-aware task scheduling scheme in which a priority model is constructed to sort the order of tasks being served based on its deadline,and then a delay-optimal collaborative offloading scheme is derived such that the tasks which cannot be completed locally can be migrated to other idle satellites.Simulation results demonstrate the effective-ness of our multi-satellite collaborative computation offloading strategy in reducing task complement time and improving resource utilization of the LEO satellite network.

High performance receiving and processing technology in satellite beam hopping communication

Beam-hopping technology has become one of the major research hotspots for satellite communication in order to enhance their communication capacity and flexibility.However,beam hopping causes the traditional continuous time-division multiplexing signal in the forward downlink to become a burst signal,satellite terminal receivers need to solve multiple key issues such as burst signal rapid synchronization and high-per-formance reception.Firstly,this paper analyzes the key issues of burst communication for traffic signals in beam hopping sys-tems,and then compares and studies typical carrier synchro-nization algorithms for burst signals.Secondly,combining the requirements of beam-hopping communication systems for effi-cient burst and low signal-to-noise ratio reception of downlink signals in forward links,a decoding assisted bidirectional vari-able parameter iterative carrier synchronization technique is pro-posed,which introduces the idea of iterative processing into car-rier synchronization.Aiming at the technical characteristics of communication signal carrier synchronization,a new technical approach of bidirectional variable parameter iteration is adopted,breaking through the traditional understanding that loop struc-tures cannot adapt to low signal-to-noise ratio burst demodula-tion.Finally,combining the DVB-S2X standard physical layer frame format used in high throughput satellite communication systems,the research and performance simulation are con-ducted.The results show that the new technology proposed in this paper can significantly shorten the carrier synchronization time of burst signals,achieve fast synchronization of low signal-to-noise ratio burst signals,and have the unique advantage of flexible and adjustable parameters.

A Method of Generating Semi-Experimental Biomedical Datasets

This paper proposed a method to generate semi-experimental biomedical datasets based on full-wave simulation software.The system noise such as antenna port couplings is fully considered in the proposed datasets,which is more realistic than synthetical datasets.In this paper,datasets containing different shapes are constructed based on the relative permittivities of human tissues.Then,a back-propagation scheme is used to obtain the rough reconstructions,which will be fed into a U-net convolutional neural network(CNN)to recover the high-resolution images.Numerical results show that the network trained on the datasets generated by the proposed method can obtain satisfying reconstruction results and is promising to be applied in real-time biomedical imaging.

An Efficient Radar Detection Method of Maneuvering Small Targets

Detection of maneuvering small targets has always been an important yet challenging task for radar signal processing.One primary reason is that target variable motions within coherent processing interval generate energy migrations across multiple resolution bins,which severely deteriorate the parameter estimation performance.A coarse-to-fine strategy for the detection of maneuvering small targets is proposed.Integration of small points segmented coherently is performed first,and then an optimal inter-segment integration is utilized to derive the coarse estimation of the chirp rate.Sparse fractional Fourier transform(FrFT)is then employed to refine the coarse estimation at a significantly reduced computational complexity.Simulation results verify the proposed scheme that achieves an efficient and reliable maneuvering target detection with-16dB input signal-to-noise ratio(SNR),while requires no exact a priori knowledge on the motion parameters.

A Residual Frequency Offset Estimation Method Based on Range Migration Fitting

Recently,researchers have proposed an emitter localization method based on passive synthetic aperture.However,the unknown residual frequency offset(RFO)between the transmit-ter and the receiver causes the received Doppler signal to shift,which affects the localization accu-racy.To solve this issue,this paper proposes a RFO estimation method based on range migration fitting.Due to the high frequency modulation slope of the linear frequency modulation(LFM)-mod-ulation radar signal,it is not affected by RFO in range compression.Therefore,the azimuth time can be estimated by fitting the peak value position of the pulse compression in range direction.Then,the matched filters are designed under different RFOs.When the zero-Doppler time obtained by the matched filters is consistent with the estimated azimuth time,the given RFO is the real RFO between the transceivers.The simulation results show that the estimation error of azimuth distance does not exceed 20 m when the received signal duration is not less than 3 s,the pulse repe-tition frequency(PRF)of the transmitter radar signal is not less than 1 kHz,the range detection is not larger than 1000 km,and the signal noise ratio(SNR)is not less than-5 dB.

High Resolution Radar Real-Time Signal and Information Processing

Radar is an electronic device that uses radio waves to determine the range, angle, or velocity of objects. Real-time signal and information processor is an important module for real-time positioning, imaging, detection and recognition of targets. With the development of ultra-wideband technology, synthetic aperture technology, signal and information processing technology, the radar coverage, detection accuracy and resolution have been greatly improved, especially in terms of one-dimensional(1D) high-resolution radar detection, tracking, recognition, and two-dimensional(2D) synthetic aperture radar imaging technology. Meanwhile, for the application of radar detection and remote sensing with high resolution and wide swath, the amount of data has been greatly increased. Therefore, the radar is required to have low-latency and real-time processing capability under the constraints of size, weight and power consumption. This paper systematically introduces the new technology of high resolution radar and real-time signal and information processing. The key problems and solutions are discussed, including the detection and tracking of 1D high-resolution radar, the accurate signal modeling and wide-swath imaging for geosynchronous orbit synthetic aperture radar, and real-time signal and information processing architecture and efficient algorithms. Finally, the latest research progress and representative results are presented, and the development trends are prospected.

Constant envelope FrFT OFDM: spectral and energy efficiency analysis

Constant envelope with a fractional Fourier transformorthogonal frequency division multiplexing(CE-FrFT-OFDM)is a special case of a constant envelope OFDM(CE-OFDM),both being energy efficient wireless communication techniques with a 0 dB peak to average power ratio(PAPR).However,with the proper selection of fractional order,the first technique has a high bit error rate(BER)performance in the frequency-time selective channels.This paper performs further analysis of CE-FrFT-OFDM by examining its spectral efficiency(SE)and energy efficiency(EE)and compare to the famous OFDM and FrFT-OFDM techniques.Analytical and comprehensive simulations conducted show that,the CE-FrFT-OFDM has five times the EE of OFDM and FrFT-OFDM systems with a slightly less SE.Increasing CE-FrFT-OFDM’s transmission power by increasing its amplitude to 1.7 increases its SE to match that of the OFDM and FrFT-OFDM systems while slightly reducing its EE by 20%to be four times that of OFDM and FrFTOFDM systems.OFDM and FrFT-OFDM’s amplitude fluctuations cause rapid changing output back-off(OBO)power requirements and further reduce power amplifier(PA)efficiency while CE-FrFTOFDM stable operational linear range makes it a better candidate and outperforms the other techniques when their OBO exceeds 1.7.Higher EE and low BER in time-frequency selective channel are attracting features for CE-FrFT-OFDM deployment in mobile devices.

DOA estimation of coexisted noncoherent and coherent signals via sparse representation of cleaned array covariance matrix

A new direction finding method is presented to deal with coexisted noncoherent and co- herent signals without smoothing operation. First the direction-of-arrival （DOA） estimation task is herein reformulated as a sparse reconstruction problem of the cleaned array covariance matrix, which is processed to eliminate the affection of the noise. Then by using the block of matrices, the information of DOAs which we pursuit are implied in the sparse coefficient matrix. Finally, the sparse reconstruction problem is solved by the improved M-FOCUSS method, which is applied to the situation of block of matrices. This method outperforms its data domain counterpart in terms of noise suppression, and has a better performance in DOA estimation than the customary spatial smoothing technique. Simulation results verify the efficacy of the proposed method.

Design of high-performance energy integrator detector for wideband radar

Target detection for wideband radar has recently received extensive attention. The classical energy integrating(EI)detector will always accumulate excess clutter or noise energy,which leads to unacceptable performance deterioration if the detection window is not selected properly. In this paper, an EI detector for the distributed targets in the Gaussian environment is proposed.First, at the stage of preparatory work, the target models are proposed, then, the problem formulation is introduced. Subsequently,in the aspect of optimizing the method of detection window search and the method of threshold setting, the detailed design stages of the proposed detector are provided. Furthermore, theoretical analyses show that the proposed detector is easy to hardware implementation, and it does not need the prior knowledge about the spatial distribution of the target scattering centers in practical radar detection application. Finally, the performance assessment conducted by Monte Carlo simulations verifies that the proposed detector outperforms the conventional detectors.

Partition of GB-InSAR deformation map based on dynamic time warping and k-means

Ground-based interferometric synthetic aperture radar(GB-InSAR)can take deformation measurement with a high accuracy.Partition of the GB-InSAR deformation map benefits analyzing the deformation state of the monitoring scene better.Existing partition methods rely on labelled datasets or single deformation feature,and they cannot be effectively utilized in GBInSAR applications.This paper proposes an improved partition method of the GB-InSAR deformation map based on dynamic time warping(DTW)and k-means.The DTW similarities between a reference point and all the measurement points are calculated based on their time-series deformations.Then the DTW similarity and cumulative deformation are taken as two partition features.With the k-means algorithm and the score based on multi evaluation indexes,a deformation map can be partitioned into an appropriate number of classes.Experimental datasets of West Copper Mine are processed to validate the effectiveness of the proposed method,whose measurement points are divided into seven classes with a score of 0.3151.

Wideband radar detector based on characteristic parameters of echoes

The statistical characterization of radar range cells with the target signals is much more distinct than that of the range cells with noise-only signals.Hence,the quasi-optimal detection principle based on the characteristic parameters of echo signals is adopted to develop a detector of range-spread targets in Gaussian noise.Firstly,the characteristic parameters of the return signals in the entire range profiles of radar are investigated.Secondly,the clustering analysis of the characteristic parameter matrix is discussed to extract the test statistic of echoes.Finally,the probabilities of detection and false alarm of the proposed detector are provided.Theoretical analysis shows that the proposed detector does not need the prior knowledge about the spatial distribution of the target scattering centers in practical scenarios,and it is simple and robust even in low signal-to-noise ratio(low-SNR)scenarios.Monte Carlo(MC)simulations reveal that the detection performance of the proposed detector outperforms the conventional detectors.

Combined algorithm of acquisition and anti-jamming based on SFT

A communication and navigation receiver is required to remove hostile jamming signals and synchronize receiving signals effectively especially for satellite communication and navigation whose resources are becoming more and more limited. This paper proposes a novel signal receiving method by combining the pro- cesses of anti-jamming and synchronization to reduce the overall computationa~ complexity at the expense of slightly affecting the detection probability, which is analyzed in detail by derivations. Furthermore, this paper introduces sparse Fourier transformation （SFT） into the proposed algorithm to replace fast Fourier transfor- mation （FFT） so as to further reduce the calculation time especially in large frequency offset environments.

Tracking error analysis and simulation of FLL-assisted PLL

In order to solve problems in high dynamic environment, a frequency-locked loop （FLL） assisted phase-locked loop （PLL） is put forward for carrier tracking. On the basis of the analysis of discriminators, the total phase error of the tracking loop is analyzed and a general error expression is derived. By using linearization and Jaffe-Rechtin coefficients, the performance of a special first order FLL-assisted second order PLL is analyzed to get a closed expression. Analysis results and simula- tions show that there exist an optimal FLL loop bandwidth and a optimal PLL loop bandwidth which can make the phase jitter much less than that when the PLL is used alone.